Are you ready to escape the abandoned mine?

Step into the ultimate Data Escape Room challenge and crack the code! In this interactive session, teams will race against the clock to solve real-world data problems using the skills and insights they’ve gained throughout the day. Collaborate, strategize, and think fast—only the sharpest minds will escape.

It’s now over six years since the emergence of the paper "How to Move Beyond a Monolithic Data Lake to a Distributed Data Mesh” by Zhamak Dehghani that had a major impact on the data and analytics industry. 

It highlighted major data architecture failures and called for a rethink in data architecture and in data provisioning by creating a data supply chain and democratising data engineering to enable business domain-oriented creation of reusable data products to make data products available as self-governing services. 

Since then, we have seen many companies adopt Data Mesh strategies, and the repositioning of some software products as well as the emergence of new ones to emphasize democratisation. But is what has happened since totally addressing the problems that Data Mesh was intending to solve? And what new problems are arising as organizations try to make data safely available to AI projects at machine-scale?  

In this unmissable session Big Data LDN Chair Mike Ferguson sits down with Zhamak Dehghani to talk about what has happened since Data Mesh emerged. It will look at:

● The drivers behind Data Mesh

● Revisiting Data Mesh to clarify on what a data product is and what Data Mesh is intending to solve

● Did data architecture really change or are companies still using existing architecture to implement this?

● What about technology to support this - Is Data Fabric the answer or best of breed tools? 

● How critical is organisation to successful Data Mesh implementation

● Roadblocks in the way of success e.g., lack of metadata standards

● How does Data Mesh impact AI?

● What’s next on the horizon?

Data governance can feel like rules slowing you down – but done well, it does the opposite. It gives clarity, builds trust, and lets teams move faster with less risk.

This interactive session will explore how to make governance practical, human, and useful in your day-to-day work. We’ll focus on the real decisions people make every day, how to clarify ownership, and how to overcome common blockers without adding unnecessary overhead.

Through scenario-based exercises and a simple governance mapping activity, you’ll leave with actionable steps to take back to your organisation – helping you turn governance from a box-ticking exercise into a genuine business enabler.

Following on from the Building consumable data products keynote, we will dive deeper into the interactions around the data product catalog, to show how the network effect of explicit data sharing relationships starts to pay dividends to the participants. Such as:

For the product consumer:

• Searching for products, understanding content, costs, terms and conditions, licenses, quality certifications etc

• Inspecting sample data, choosing preferred data format, setting up a secure subscription, and seeing data provisioned into a database from the product catalog.

• Providing feedback and requesting help

• Reviewing own active subscriptions

• Understanding the lineage behind each product along with outstanding exceptions and future plans

For the product manager/owner:

• Setting up a new product, creating a new release of an existing product and issuing a data correction/restatement

• Reviewing a product’s active subscriptions and feedback/requests from consumers

• Interacting with the technical teams on pipeline implementations along with issues and proposed enhancements

• For the data governance team

• Viewing the network of dependencies between data products (the data mesh) to understand the data value chains and risk concentrations

• Reviewing a dashboard of metrics around the data products including popularity, errors/exceptions, subscriptions, interaction

• Show traceability from a governance policy relating to, say data sovereignty or data privacy to the product implementations.

• Building trust profiles for producers and consumers

The aim of the demonstrations and discussions is to explore the principles and patterns relating to data products, rather than push a particular implementation approach.

Having said that, all of the software used in the demonstrations is open source. Principally this is Egeria, Open Lineage and Unity Catalog from the Linux Foundation, plus Apache Airflow, Apache Kafka and Apache SuperSet from the Apache Software Foundation.  

Videos of the demonstrations will be available on YouTube after the conference and the complete demo software can be downloaded and run on a laptop so you can share your experiences with your teams after the event.

In this interactive workshop, Sunil Soares will break down the key learning points from the morning's keynote session, exploring real-world embedded AI applications, and unpack how regulations like the EU AI Act impact autonomous systems. You’ll leave with practical tools and explore how to govern AI responsibly—without slowing innovation.

AI agents have seen increasing adoption across multiple industries as the next wave of AI. Existing regulations such as the European Union AI Act also apply to AI agents.

The session is based on Sunil Soares' books that can be found here: https://yourdataconnect.com

This session will cover the following topics:

• Agentic AI governance framework

• Applications with embedded AI

• Associated AI Governance Regulations including EU AI Act

• Agentic AI Governance Platforms

When data users choose to circumvent official sources of data, it increases the risks to the organisation. How do you encourage teams to share data widely, effectively and legally? Are data products the answer? We explore the data sharing user journey to highlight the key features of a data product strategy that significantly improves the effectiveness of your data.

In today’s fast-moving global business environment, technological innovation, shifting consumer demands, and the growing imperative of sustainability are redefining how organizations operate and compete. To thrive in this dynamic landscape, businesses must place data at the core of their strategic and operational decisions, embracing digital tools, AI, and automation to unlock productivity and resilience.

This engaging presentation offers a powerful framework for building a tailored data strategy aligned with organizational goals. Led by an expert with over two decades of strategic leadership experience across Fortune 500 companies, FTSE 100 firms, non-profits, and SMEs, this session combines real-world insights with actionable tools to help you navigate complexity and drive sustained growth.

Whether you’re developing a data strategy from the ground up or enhancing an existing approach, this session will empower you to lead with clarity, drive innovation, and future-proof your business.

Key Takeaways:

• Emerging Trends: Discover how to integrate disruptive technologies, including AI, into your data strategy.

• Innovation Blueprints: Learn to create a culture of creativity, confidence, and capability.

• Strategic Foundations: Explore the essential building blocks of a successful data strategy.

• Global Perspectives: Benefit from international case studies of both triumphs and lessons learned.

• Interactive Q&A: Bring your challenges to the table and gain expert advice and fresh perspectives.

If you’re serious about making smarter decisions, driving growth, and staying ahead of the curve — this session is for you.

A welcome address to the first edition of Data Driven LDN, from Big Data LDN Chair, Mike Ferguson.

In this brief introduction, Mike will outline the agenda for the day, and introduce the key topics that will be discussed.